{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_3000 = pd.read_csv('./train_3000_avg_pred.csv')\n",
    "pred_30465 = pd.read_csv('./train_30465_avg_pred.csv')\n",
    "pred_33465 = pd.read_csv('./train_33465_avg_pred.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #\n",
    "# plt.figure(figsize=(20,10))\n",
    "# plt.subplot(121)\n",
    "# plt.plot(pred_3000.id, pred_3000.score)\n",
    "# plt.title('pred_3000')\n",
    "# plt.subplot(122)\n",
    "# plt.plot(pred_33465.id, pred_33465.score)\n",
    "# plt.title('pred_30465')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fc4b05674a8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w1, w2, w3 = 0.15, 0.1, 0.75\n",
    "plt.figure(figsize=(10,8))\n",
    "sns.distplot(pred_3000.score)\n",
    "sns.distplot(pred_30465.score)\n",
    "sns.distplot(pred_33465.score)\n",
    "sns.distplot(w1*pred_3000.score + w2*pred_30465.score + w3*pred_33465.score)\n",
    "plt.legend(['pred_3000','pred_30465','pred_33465','combine'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "com_score = w1*pred_3000.score + w2*pred_30465.score + w3*pred_33465.score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_all = pred_3000[['id']].copy()\n",
    "pred_all['label'] = com_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upper: 0.2745436365499999  downer: 0.12138716671999998\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "upper = np.percentile(com_score,95)\n",
    "downer = np.percentile(com_score,10)\n",
    "print('upper:',upper,' downer:',downer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_all.loc[(pred_all.label>upper).values,'label']=1\n",
    "pred_all.loc[(pred_all.label<downer).values,'label']=0\n",
    "filter = (pred_all.label>upper)|(pred_all.label<downer)\n",
    "\n",
    "# filter = pred_all.label>upper\n",
    "pred_selec= pred_all.iloc[filter.values]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_selec = pred_selec.astype({'label':np.int64})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5323"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unlabel_y = pred_selec.reset_index(drop=True)\n",
    "sum(unlabel_y.label==1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "unlabel_y.to_csv('unlabel_y.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
